64-slice CT Research Articles

Evaluation of mitral chordae tendineae length using four-dimensional computed tomography.

Mitral valvuloplasty using artificial chordae tendineae represents an effective surgical approach for treating mitral regurgitation. Achieving precise measurements of artificial chordae tendineae length (CL) is an important factor in the procedure; however, no objective index currently exists to facilitate this measurement. Therefore, preoperative assessment of CL is critical for surgical planning and support. Four-dimensional x-ray micro-computed tomography (4D-CT) may be useful for accurate CL measurement considering that it allows for dynamic three-dimensional (3D) evaluation compared to that with transthoracic echocardiography, a conventional inspection method. To investigate the behavior and length of mitral chordae tendineae during systole using 4D-CT. Eleven adults aged > 70 years without mitral valve disease were evaluated. A 64-slice CT scanner was used to capture 20 phases in the cardiac cycle in electrocardiographic synchronization. The length of the primary chordae tendineae was measured from early systole to early diastole using the 3D image. The primary chordae tendineae originating from the anterior papillary muscle and attached to the A1-2 region and those from the posterior papillary muscle and attached to the A2-3 region were designated as cA and cP, respectively. The behavior and maximum lengths [cA (ma), cP (max)] were compared, and the correlation with body surface area (BSA) was evaluated. In all cases, the mitral anterior leaflet chordae tendineae could be measured. In most cases, the cA and cP chordae tendineae could be measured visually. The mean cA (max) and cP (max) were 20.2 mm ± 1.95 mm and 23.5 mm ± 4.06 mm, respectively. cP (max) was significantly longer. The correlation coefficients (r) with BSA were 0.60 and 0.78 for cA (max) and cP (max), respectively. Both cA and cP exhibited constant variation in CL during systole, with a maximum 1.16-fold increase in cA and a 1.23-fold increase in cP from early to mid-systole. For cP, CL reached a plateau at 15% and remained elongated until end-systole, whereas for cA, after peaking at 15%, CL shortened slightly and then moved toward its peak again as end-systole approached. The study suggests that 4D-CT is a valuable tool for accurate measurement of both the length and behavior of chordae tendineae within the anterior leaflet of the mitral valve.

AATCT-IDS: A benchmark Abdominal Adipose Tissue CT Image Dataset for image denoising, semantic segmentation, and radiomics evaluation

Background and objective:The metabolic syndrome induced by obesity is closely associated with cardiovascular disease, and the prevalence is increasing globally, year by year. Obesity is a risk marker for detecting this disease. However, current research on computer-aided detection of adipose distribution is hampered by the lack of open-source large abdominal adipose datasets. Methods:In this study, a benchmark Abdominal Adipose Tissue CT Image Dataset (AATCT-IDS) containing 300 subjects is prepared and published. AATCT-IDS publics 13,732 raw CT slices, and the researchers individually annotate the subcutaneous and visceral adipose tissue regions of 3213 of those slices that have the same slice distance to validate denoising methods, train semantic segmentation models, and study radiomics. For different tasks, this paper compares and analyzes the performance of various methods on AATCT-IDS by combining the visualization results and evaluation data. Thus, verify the research potential of this data set in the above three types of tasks. Results:In the comparative study of image denoising, algorithms using a smoothing strategy suppress mixed noise at the expense of image details and obtain better evaluation data. Methods such as BM3D preserve the original image structure better, although the evaluation data are slightly lower. The results show significant differences among them. In the comparative study of semantic segmentation of abdominal adipose tissue, the segmentation results of adipose tissue by each model show different structural characteristics. Among them, BiSeNet obtains segmentation results only slightly inferior to U-Net with the shortest training time and effectively separates small and isolated adipose tissue. In addition, the radiomics study based on AATCT-IDS reveals three adipose distributions in the subject population. Conclusion:AATCT-IDS contains the ground truth of adipose tissue regions in abdominal CT slices. This open-source dataset can attract researchers to explore the multi-dimensional characteristics of abdominal adipose tissue and thus help physicians and patients in clinical practice. AATCT-IDS is freely published for non-commercial purpose at: https://figshare.com/articles/dataset/AATTCT-IDS/23807256.

Mask-aware transformer with structure invariant loss for CT translation

Multi-phase enhanced computed tomography (MPECT) translation from plain CT can help doctors to detect the liver lesion and prevent patients from the allergy during MPECT examination. Existing CT translation methods directly learn an end-to-end mapping from plain CT to MPECT, ignoring the crucial clinical domain knowledge. As clinicians subtract the plain CT from MPECT images as subtraction image to highlight the contrast-enhanced regions and further to facilitate liver disease diagnosis in the clinical diagnosis, we aim to exploit this domain knowledge for automatic CT translation. To this end, we propose a Mask-Aware Transformer (MAFormer) with structure invariant loss for CT translation, which presents the first effort to exploit this domain knowledge for CT translation. Specifically, the proposed MAFormer introduces a mask estimator to predict the subtraction image from the plain CT image. To integrate the subtraction image into the network, the MAFormer devises a Mask-Aware Transformer based Normalization (MATNorm) as normalization layer to highlight the contrast-enhanced regions and capture the long-range dependencies among these regions. Moreover, aiming to preserve the biological structure of CT slices, a structure invariant loss is designed to extract the structural information and minimize the structural similarity between the plain and synthetic CT images to ensure the structure invariant. Extensive experiments have proven the effectiveness of the proposed method and its superiority to the state-of-the-art CT translation methods. Source code is to be released.

Absorbed dose, effective dose and lifetime attributable risk of breast and thyroid cancers in coronary CT angiography: A comparison between 64 and 128 slice CT scanners

The attentive consideration of absorbed dose impact on the breast, a radiosensitive organ, remains pivotal in coronary computed tomography angiography (CCTA). Additionally, the thyroid is subjected to scatter radiation during this diagnostic procedure. The primary objective of this study was to comprehensively investigate and quantify the absorbed dose, effective dose, and lifetime attributable risks (LARs) associated with breast and thyroid cancers in the context of CCTA. This investigation enrolled a cohort of 180 patients (90 men and 90 women) who underwent CCTA utilizing three distinct CT scanners: the SOMATOM Definition AS 128 slice (Siemens 128), the Lightspeed VCT 64 Slice (GE 64), and the Brilliance 64 Slice (Philips 64). The precise quantification of absorbed doses to the breast and thyroid was achieved through the utilization of a thermoluminescence dosimeter (TLD). LAR for breast and thyroid cancers was evaluated in accordance with the BEIR VII report. Kruskal–Wallis test was employed to compare the means of absorbed doses and LARs. The average absorbed doses to the breast during CCTA with Siemens 128, GE 64, and Philips 64 scanners were 116.32 ± 39.02, 82.88 ± 18.33, and 84.11 ± 15.18 mGy, respectively (P < 0.05). Correspondingly, the average LAR for breast cancer was found to be 84, 68, and 52 cases per 100,000 persons, respectively. Notably, a significant discrepancy in breast cancer LARs was observed among different age groups (P < 0.05). Regarding thyroid doses with Siemens 128, GE 64, and Philips 64 scanners, average values were 11.82 ± 7.51, 12.20 ± 10.87, and 14.49 ± 5.43 mGy, respectively (P > 0.05). Additionally, the average LAR for thyroid cancer was determined as 0.32, 0.56, and 0.22 cases per 100,000 persons, respectively. Across all age groups, the LAR for thyroid cancer exhibited higher values among women compared to men. However, these differences did not achieve statistical significance (P > 0.05), indicating a need for further investigation. The findings prominently indicated high absorbed doses to the breast in CCTA using protocols investigated in this study (with an average of 93.7 ± 30.26 mGy). Particularly, the LAR for breast cancer was higher among younger women, specifically those aged between 20 and 40 years (249 cases per 100,000). These results underscore the necessity for further justification and optimization of CCTA protocols.

Unveiling tumor invasiveness: enhancing cancer diagnosis with phase-contrast microtomography for 3D virtual histology

Malignant diseases are characterized by a critical trait known as invasiveness, where tumor cells tend to spread from the primary tissue layer into surrounding healthy tissues and distant organs. Presently, histopathology offers essential insights for diagnosing, classifying, predicting outcomes, and guiding patient-specific treatments. However, histology offers two-dimensional data from chosen cutting planes. Although 3D histological volumes can be generated through serial sectioning or whole slide imaging, this method is laborious, may introduce processing artefacts, and lacks isotropic spatial resolution. These limitations pose a considerable challenge to accurate diagnoses, particularly when dealing with micro-infiltrating carcinomas. These lesions, characterized by minute infiltrations, demand a three-dimensional representation for comprehensive visualization, essential for precise identification and assessment. Emerging X-ray-based virtual histology technology offers three-dimensional visualization of soft-tissue specimens, enabling virtual slicing in any direction or at any point. This approach can assist in guiding tissue sectioning for optimal representation of tumor cross sections during histological analysis. Micro-infiltrating carcinomas from the breast, cervix, and thyroid were imaged using X-ray phase-contrast microtomography (PhC-μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT) at the Elettra synchrotron facility in Trieste, Italy. Comparative assessment of histological and CT slices by pathologists revealed that PhC-μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mu$$\\end{document}CT aids in classifying lesions by highlighting distinct tissue components and, notably, identifying tissue invasion. Reviewing a volume image allows pathologists to trace the entire lesion, identifying invasion sites that might be overlooked in individual or serial histological sections. Consequently, this proposed method could complement pathologists’ tools, potentially enhancing diagnoses by minimizing under-staging and reducing false negative results.

CLASSIFICATION OF FREIBERG'S DISEASE: A GUIDE FOR MANAGEMENT

IntroductionThe current treatment for Freiberg's osteochondrosis centres around either: simple debridement or debridement osteotomy. The main principle of the osteotomy is to rotate normal articular cartilage into the affected area. We recommend the use of CT scanning to delineate the amount of available, unaffected cartilage available to rotate into the affected space.MethodsWe retrospectively reviewed 32 CT scans of new Freiberg's diagnoses in Sheffield over a 10 year period using the PACS system. We identified the sagittal CT slice that displayed the widest portion of proximal articular margin of the proximal phalanx and measured the diseased segment of the corresponding metatarsal head as an arc (in degrees). This arc segment was divided by 360°. This gave a ratio of the affected arc in the sagittal plane.Results28 out of 32 cases involved the 2nd metatarsal with the remaining 4 involving the 3rd metatarsal head. Of 32 cases, 18 had fragmentation. Surgically, 20 had debridement only, 5 also had an osteotomy and 1 had a fusion. 6 of the 32 cases were managed non-operatively. 11 cases out of 32 had an arc ratio of &lt; 0.3. Of these, only 3 had an osteotomy, 3 had no procedure and 5 had a simple debridement. Of those that had osteotomies (5/32), 3 of the 5 cases had an arc ratio of &lt; 0.3 with the other 2 being 0.42 and 0.38.DiscussionWe hypothesise that those cases with an arc ratio of less 0.3 would be amenable to a dorsal closing wedge osteotomy and those with a ratio of more than 0.4 would be better suited to a simple debridement. For those cases between 0.3–0.4, we feel either option is viable. Further work to prove or disprove outcomes related to our classification is required.

Comparison of virtual reality and computed tomography in the preoperative planning of complex tibial plateau fractures

IntroductionPreoperative planning is a critical step in the success of any complex surgery. The pur-pose of this study is to evaluate the advantage of VR glasses in surgical planning of complex tibial plateau fractures compared to CT planning.Materials and methodsFive orthopedic surgeons performed preoperative planning for 30 fractures using either conventional CT slices or VR visualization with a VR headset. Planning was performed in a randomized order with a 3-month interval between planning sessions. A standardized questionnaire assessed planned operative time, planning time, fracture classification and understanding, and surgeons’ subjective confidence in surgical planning.ResultsThe mean planned operative time of 156 (SD 47) minutes was significantly lower (p < 0.001) in the VR group than in the CT group (172 min; SD 44). The mean planning time in the VR group was 3.48 min (SD 2.4), 17% longer than in the CT group (2.98 min, SD 1.9; p = 0.027). Relevant parameters influencing planning time were surgeon experience (-0.61 min) and estimated complexity of fracture treatment (+ 0.65 min).ConclusionThe use of virtual reality for surgical planning of complex tibial plateau fractures resulted in significantly shorter planned operative time, while planning time was longer compared to CT planning. After VR planning, more surgeons felt (very) well prepared for surgery.

Abstract PO1-11-11: A Novel Body Composition Risk Score (B-Score) and Overall Survival among Patients with Early-Stage Breast Cancer

Abstract Background: Measurements (amount, distribution, and radiodensity) of muscle and adipose tissue were reported to be individually associated with overall survival in breast cancer survivors, but they were not typically combined to develop an overall risk score. Such a score can identify patients at high risk of death and prioritize patients in need of lifestyle interventions. Objectives: We developed a novel body composition risk score (B-Score) by combining multiple tissue measurements. Methods: We included 3105 patients with stage II or III breast cancer (diagnosed from 2000 to 2013) at Kaiser Permanente Northern California and Dana Farber Cancer Institute. From CT scans at diagnosis, we used the third lumber vertebrae as the landmark to assess areas (cm2) and radiodensity (HU) of muscle and adipose tissue. We divided the area by height2 (m2) to derive the index and measured the average HU of the tissue area as the radiodensity, which acts as a marker of tissue 'quality' to be indicative of lipid content, inflammation, and angiogenesis. Out of all tissue measurements, we considered skeletal muscle index (SMI), subcutaneous adipose tissue index (SATI) and SAT radiodensity as they were independent predictors for overall survival. Each measurement was dichotomized using optimal stratification, with low SMI (&amp;lt; 40.1cm2/m2), high SATI (≥75.7cm2/m2), and high SAT radiodensity (≥ -97.2HU) considered risk factors. We calculated B-Score as the sum of these factors and estimated its association with overall survival using Cox proportional hazards regression with adjustment for clinicopathologic factors. Results: Mean (standard deviation) age at diagnosis was 53.9 (11.8) years, 2161 (70.1%) were Non-Hispanic White, 1880 (60.5%) were stage II, and 919 (29.6%) died over a median follow-up of 10.7 years. Most patients (60.6%) had only one body composition risk factor (B-Score = 1). Compared to those with no body composition risk factors (B-Score = 0), the risk of death increased with more body composition risk factors: the adjusted hazard ratios were 1.10 (95% CI: 0.85, 1.42), 1.47 (95% CI: 1.12, 1.92), and 2.11 (95% CI: 1.26, 3.53) for B-Scores of 1, 2, and 3, respectively (Ptrend &amp;lt; 0.001). Conclusions: More unfavorable body composition characteristics were associated with increased risks of overall mortality in a dose-response manner. Considering body composition measurements together as a composite score (B-Score) may prove a useful tool to identify patients at high risk of death following breast cancer diagnosis. Table. Adjusted Associations of the Body Composition Risk Score (B-Score) with Overall Mortality Among Patients with Early-Stage Breast Cancer Abbreviations: HR, hazard ratio. a Areas (cm2) and radiodensity (HU) of skeletal muscle and subcutaneous adipose tissue (SAT) were extracted from the single axial CT slice at the third lumbar vertebra. The body composition risk score was defined as the sum of three risk factors: low skeletal muscle index (SMI; &amp;lt;40.1cm2/m2), high SAT index (SATI; ≥75.7cm2/m2), and high SAT radiodensity (≥ -97.2HU). b Adjusted for age (years), race and ethnicity (Asian, Black, Hispanic, Non-Hispanic White, and Others), stage (II, III), ER (ER+, ER-), PR (PR+, PR-), HER2 (HER2+, HER2-, unknown), smoking (current, former, never), Charlson comorbidity index (0, 1-2, ≥3), and BMI (&amp;lt;18.5, 28.5-24.9, 25-29.9, and ≥30 kg/m2). For the trend test, B-Score was considered as a continuous variable with adjustment for the above covariates. Citation Format: En Cheng, Bette Caan, Wendy Chen, Carla Prado, Elizabeth Cespedes Feliciano. A Novel Body Composition Risk Score (B-Score) and Overall Survival among Patients with Early-Stage Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-11-11.

A novel approach for estimating lung tumor motion based on dynamic features in 4D-CT

Due to the high expenses involved, 4D-CT data for certain patients may only include five respiratory phases (0%, 20%, 40%, 60%, and 80%). This limitation can affect the subsequent planning of radiotherapy due to the absence of lung tumor information for the remaining five respiratory phases (10%, 30%, 50%, 70%, and 90%). This study aims to develop an interpolation method that can automatically derive tumor boundary contours for the five omitted phases using the available 5-phase 4D-CT data. The dynamic mode decomposition (DMD) method is a data-driven and model-free technique that can extract dynamic information from high-dimensional data. It enables the reconstruction of long-term dynamic patterns using only a limited number of time snapshots. The quasi-periodic motion of a deformable lung tumor caused by respiratory motion makes it suitable for treatment using DMD. The direct application of the DMD method to analyze the respiratory motion of the tumor is impractical because the tumor is three-dimensional and spans multiple CT slices. To predict the respiratory movement of lung tumors, a method called uniform angular interval (UAI) sampling was developed to generate snapshot vectors of equal length, which are suitable for DMD analysis. The effectiveness of this approach was confirmed by applying the UAI-DMD method to the 4D-CT data of ten patients with lung cancer. The results indicate that the UAI-DMD method effectively approximates the lung tumor’s deformable boundary surface and nonlinear motion trajectories. The estimated tumor centroid is within 2 mm of the manually delineated centroid, a smaller margin of error compared to the traditional BSpline interpolation method, which has a margin of 3 mm. This methodology has the potential to be extended to reconstruct the 20-phase respiratory movement of a lung tumor based on dynamic features from 10-phase 4D-CT data, thereby enabling more accurate estimation of the planned target volume (PTV).

HRU-Net: A high-resolution convolutional neural network for esophageal cancer radiotherapy target segmentation

Background and objectiveThe effective segmentation of esophageal squamous carcinoma lesions in CT scans is significant for auxiliary diagnosis and treatment. However, accurate lesion segmentation is still a challenging task due to the irregular form of the esophagus and small size, the inconsistency of spatio-temporal structure, and low contrast of esophagus and its peripheral tissues in medical images. The objective of this study is to improve the segmentation effect of esophageal squamous cell carcinoma lesions. MethodsIt is critical for a segmentation network to effectively extract 3D discriminative features to distinguish esophageal cancers from some visually closed adjacent esophageal tissues and organs. In this work, an efficient HRU-Net architecture (High-Resolution U-Net) was exploited for esophageal cancer and esophageal carcinoma segmentation in CT slices. Based on the idea of localization first and segmentation later, the HRU-Net locates the esophageal region before segmentation. In addition, an Resolution Fusion Module (RFM) was designed to integrate the information of adjacent resolution feature maps to obtain strong semantic information, as well as preserve the high-resolution features. ResultsCompared with the other five typical methods, the devised HRU-Net is capable of generating superior segmentation results. ConclusionsOur proposed HRU-NET improves the accuracy of segmentation for squamous esophageal cancer. Compared to other models, our model performs the best. The designed method may improve the efficiency of clinical diagnosis of esophageal squamous cell carcinoma lesions.

Parameters That Can Be Used to Quantify Reduction Accuracy in Talar Neck Fractures and Malunions: A PRISMA-Compliant Scoping Review and Meta-Analysis.

Understanding the three-dimensional anatomy of the talar neck is essential in assessing the accuracy of reduction in talar neck fractures as well as for planning surgical correction for talar malunions. However, the geometrical parameters that describe this anatomy are sparsely reported in the orthopedics literature. We aimed to identify from the existing literature, geometrical parameters that describe the anatomy of the talar neck, determine how these are measured, and their normative values. A scoping literature review was conducted in accordance with thePreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)extension for scoping reviews (PRISMA-ScR) guidelines. The primary searches were conducted on the PubMed, Embase, and Scopus databases. Any original research study looking at the human talus neck geometry was included. Parameters that described the anatomy of the talar neck were identified, andpooled estimates were determined by the random-effects meta-analysis model. Heterogeneity was assessed by the I2 test and leave-one-out meta-analysis. Subgroup analysis was done to compare the values of parameters between the Asian and Non-Asian populations. The risk of bias was assessed by the National Institutes of Health (NIH) Case Series Tool. The combined searches yielded 6326 results, of which 21 studies were included in the review and 15 in six different sets of metanalysis. The majority of the studies (n=19, 90.5%) evaluated adult tali, and only two (9.5%) evaluated pediatric tali.In most of the studies (n=13, 61.9%), talus neck geometry was evaluated on dry bones or anatomical specimens; evaluation by imaging techniques (radiographs, CT, MRI, and radiostereometric analysis) was used in eight studies, (39.1%). A total of eight different geometrical parameters (neck length, height, width, declination angle, inclination angle, torsion angle, circumference, and cross-sectional area) were identified. Except for talar torsion, variability was noted in methods of measurement of all other parameters. Subgroup analysis revealed that Asians had a higher neck height as compared to non-Asians; other parameters were not significantly different. Although the literature reports geometrical parameters to assess the talar geometry, the methods of measurement of these parameters are variable. Most of the available literature describes measurement techniques on cadaveric tali, and there is no literature on how these parameters should be measured on conventional CT or MRI slices. Further research needs to focus on the standardization of measurement techniques for these parameters on conventional CT and/or MRI scans.

Voxel-wise body composition analysis using image registration of a three-slice CT imaging protocol: methodology and proof-of-concept studies

BackgroundComputed tomography (CT) is an imaging modality commonly used for studies of internal body structures and very useful for detailed studies of body composition. The aim of this study was to develop and evaluate a fully automatic image registration framework for inter-subject CT slice registration. The aim was also to use the results, in a set of proof-of-concept studies, for voxel-wise statistical body composition analysis (Imiomics) of correlations between imaging and non-imaging data.MethodsThe current study utilized three single-slice CT images of the liver, abdomen, and thigh from two large cohort studies, SCAPIS and IGT. The image registration method developed and evaluated used both CT images together with image-derived tissue and organ segmentation masks. To evaluate the performance of the registration method, a set of baseline 3-single-slice CT images (from 2780 subjects including 8285 slices) from the SCAPIS and IGT cohorts were registered. Vector magnitude and intensity magnitude error indicating inverse consistency were used for evaluation. Image registration results were further used for voxel-wise analysis of associations between the CT images (as represented by tissue volume from Hounsfield unit and Jacobian determinant) and various explicit measurements of various tissues, fat depots, and organs collected in both cohort studies.ResultsOur findings demonstrated that the key organs and anatomical structures were registered appropriately. The evaluation parameters of inverse consistency, such as vector magnitude and intensity magnitude error, were on average less than 3 mm and 50 Hounsfield units. The registration followed by Imiomics analysis enabled the examination of associations between various explicit measurements (liver, spleen, abdominal muscle, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), thigh SAT, intermuscular adipose tissue (IMAT), and thigh muscle) and the voxel-wise image information.ConclusionThe developed and evaluated framework allows accurate image registrations of the collected three single-slice CT images and enables detailed voxel-wise studies of associations between body composition and associated diseases and risk factors.

Sub-features orthogonal decoupling: Detecting bone wall absence via a small number of abnormal examples for temporal CT images

The absence of bone wall located in the jugular bulb and sigmoid sinus of the temporal bone is one of the important reasons for pulsatile tinnitus. Automatic and accurate detection of these abnormal singes in CT slices has important theoretical significance and clinical value. Due to the shortage of abnormal samples, imbalanced samples, small inter-class differences, and low interpretability, existing deep-learning methods are greatly challenged. In this paper, we proposed a sub-features orthogonal decoupling model, which can effectively disentangle the representation features into class-specific sub-features and class-independent sub-features in a latent space. The former contains the discriminative information, while, the latter preserves information for image reconstruction. In addition, the proposed method can generate image samples using category conversion by combining the different class-specific sub-features and the class-independent sub-features, achieving corresponding mapping between deep features and images of specific classes. The proposed model improves the interpretability of the deep model and provides image synthesis methods for downstream tasks. The effectiveness of the method was verified in the detection of bone wall absence in the temporal bone jugular bulb and sigmoid sinus.

ECR 2024 Abstract Highlights

The following highlights spotlight selected abstracts presented at the European Congress of Radiology (ECR) 2024. Covering a range of topics, from deep learning applications in neurological disorders to using a single cranial CT slice for identifying deceased individuals, these highlights present the latest cutting-edge developments in radiology.

Assessing variability in non-contrast CT for the evaluation of stroke: The effect of CT image reconstruction conditions on AI-based CAD measurements of ASPECTS value and hypodense volume.

To rule out hemorrhage, non-contrast CT (NCCT) scans are used for early evaluation of patients with suspected stroke. Recently, artificial intelligence tools have been developed to assist with determining eligibility for reperfusion therapies by automating measurement of the Alberta Stroke Program Early CT Score (ASPECTS), a 10-point scale with > 7 or ≤ 7 being a threshold for change in functional outcome prediction and higher chance of symptomatic hemorrhage, and hypodense volume. The purpose of this work was to investigate the effects of CT reconstruction kernel and slice thickness on ASPECTS and hypodense volume. The NCCT series image data of 87 patients imaged with a CT stroke protocol at our institution were reconstructed with 3 kernels (H10s-smooth, H40s-medium, H70h-sharp) and 2 slice thicknesses (1.5mm and 5mm) to create a reference condition (H40s/5mm) and 5 non-reference conditions. Each reconstruction for each patient was analyzed with the Brainomix e-Stroke software (Brainomix, Oxford, England) which yields an ASPECTS value and measure of total hypodense volume (mL). An ASPECTS value was returned for 74 of 87 cases in the reference condition (13 failures). ASPECTS in non-reference conditions changed from that measured in the reference condition for 59 cases, 7 of which changed above or below the clinical threshold of 7 for 3 non-reference conditions. ANOVA tests were performed to compare the differences in protocols, Dunnett's post-hoc tests were performed after ANOVA, and a significance level of p < 0.05 was defined. There was no significant effect of kernel (p = 0.91), a significant effect of slice thickness (p < 0.01) and no significant interaction between these factors (p = 0.91). Post-hoc tests indicated no significant difference between ASPECTS estimated in the reference and any non-reference conditions. There was a significant effect of kernel (p < 0.01) and slice thickness (p < 0.01) on hypodense volume, however there was no significant interaction between these factors (p = 0.79). Post-hoc tests indicated significantly different hypodense volume measurements for H10s/1.5mm (p = 0.03), H40s/1.5mm (p < 0.01), H70h/5mm (p < 0.01). No significant difference was found in hypodense volume measured in the H10s/5mm condition (p = 0.96). Automated ASPECTS and hypodense volume measurements can be significantly impacted by reconstruction kernel and slice thickness.

Forensic significance and inferential value of PMCT features in charred bodies: A bicentric study

Post-mortem computed tomography (PMCT) is a diagnostic tool that provides essential information in forensic field. This radiological technique can play a pivotal role in personal identification, gunshot injuries, major traumatic injuries, child abuse, drowning asphyxia, embolism, COVID-19, sudden death, and charring cases.Post-mortem imaging can be used to investigate charred bodies as it allows the forensic examiner to distinguish traumatic and heat injuries. PMCT images can also provide additional information to determine whether the individual was alive at the time the fire started.In our bicentric study, we performed PMCT on 15 cases of charred bodies (10 males and 5 females) collected at the Florence University (Florence, Italy) and Catholic University of The Sacred Heart (Rome, Italy) before the external examination and/or full autopsy examination. In both the institutions, PMCT was performed through a Siemens SOMATOM 16-slice CT scanner (Siemens Aktiengesellschaft, Berlin, 2010).The aim of the current study was to obtain unambiguous information that could help determine the cause of death by comparing our PMCT findings with the most recent evidence in the scientific literature. Our investigations focused on the evaluation of bone texture and differences from traumatic fractures, leading also to an improvement in the interpretation of some aspecific findings (e.g., soot) from the integration of the radiological information with the autopsy results.The data obtained in our study support PMCT as a reliable diagnostic tool in the study of charred corpses and represent basic evidence for further applications of radiology in the forensic field.

Mixed reality guided root canal therapy.

Root canal therapy (RCT) is a widely performed procedure in dentistry, with over 25 million individuals undergoing it annually. This procedure is carried out to address inflammation or infection within the root canal system of affected teeth. However, accurately aligning CT scan information with the patient's tooth has posed challenges, leading to errors in tool positioning and potential negative outcomes. To overcome these challenges, a mixed reality application is developed using an optical see-through head-mounted display (OST-HMD). The application incorporates visual cues, an augmented mirror, and dynamically updated multi-view CT slices to address depth perception issues and achieve accurate tooth localization, comprehensive canal exploration, and prevention of perforation during RCT. Through the preliminary experimental assessment, significant improvements in the accuracy of the procedure are observed. Specifically, with the system the accuracy in position was improved from 1.4 to 0.4 mm (more than a 70% gain) using an Optical Tracker (NDI) and from 2.8 to 2.4 mm using an HMD, thereby achieving submillimeter accuracy with NDI. 6 participants were enrolled in the user study. The result of the study suggests that the average displacement on the crown plane of 1.27 ± 0.83 cm, an average depth error of 0.90 ± 0.72 cm and an average angular deviation of 1.83 ± 0.83°. Our error analysis further highlights the impact of HMD spatial localization and head motion on the registration and calibration process. Through seamless integration of CT image information with the patient's tooth, our mixed reality application assists dentists in achieving precise tool placement. This advancement in technology has the potential to elevate the quality of root canal procedures, ensuring better accuracy and enhancing overall treatmentoutcomes.

Quantitative assessment of cement bridges and voids in cement-stabilized permeable base materials using a mask R-CNN-based CT image segmentation strategy

Accurate extraction of aggregates, cement bridges, and voids in permeable cement-stabilized base materials (PCBM) is a challenging task. This paper proposed a segmentation and reconstruction paradigm for raw CT slice images using a mask regional convolutional neural network (Mask R-CNN). The results demonstrate that the proposed method effectively segments and reconstructs unclear raw CT slice images, providing a convenient and advanced tool for accurately assessing the meso-scale structures of cement bridges and voids in PCBM prepared with different combinations of cement content and compaction force. An increased cement content or compaction force results in the migration of cement paste, leading to thicker localized cement bridges and blockage of permeable pore space. This phenomenon further disrupts the homogeneous distribution of cement bridges and voids. An increased compaction force tends to elongate and flatten pore throats, while an increased cement content may clog voids, rendering them impermeable. The vertical permeability of the PCBM is significantly greater than the horizontal permeability, which should be considered during material design optimization. The proposed method could serve as a reference for microscopic analysis and structural design optimization of PCBM.

Pancreatic cyst prevalence and detection with photon counting CT compared with conventional energy integrating detector CT

PurposeTo calculate the prevalence of pancreatic cysts on photon counting CT (PCCT) and compare with that of 128-slice conventional energy-integrating detector CT (EIDCT). MethodA retrospective single institution database search identified all contrast-enhanced abdominal CT examinations performed at an outpatient facility that has both a PCCT and EIDCT between 4/11/2022 and 7/26/2022. The presence and size of pancreatic cysts were recorded. In patients with PCCT reported pancreatic cysts, prior CT imaging (EIDCT) was reviewed for reported pancreatic cysts. Fisher’s exact test was used to compare the pancreatic cyst detection rate for PCCT and EIDCT. Wilcoxon rank sum test was used to compare cyst size and patient age. A p <.05 indicated statistical significance. Results2494 patients were included. Our pancreatic cyst detection rate was 4.9 % (49/1009) with PCCT and 3.0 % (44/1485) for EIDCT (p =.017). For CT angiograms, pancreatic cysts were detected in 6.6 % (21/319) with PCCT and 0.0 % (0/141) with EIDCT (p <.001). Pancreatic cyst detection rate was not statistically different for portal venous, enterography, renal mass, pancreas, 3-phase liver, or venogram protocols (all p >.05). Mean[SD] pancreatic cyst size was 13.7[9.7]mm for PCCT and 15.3[14.7] for EIDCT (p =.95). 55.1 % (27/49) of PCCT and 61.4 % (27/44) of EIDCT that described pancreatic cysts had prior contrast-enhanced EIDCTs. Of these, 40.7 % (11/27) of PCCT and 14.8 % (4/27) of EIDCT described pancreatic cysts were not previously reported (p =.027). ConclusionsPhoton-counting CT afforded greater pancreatic cyst detection than conventional energy-integrating detector CT, particularly with CT angiograms.

State-of-the-art mobile head CT scanner delivers nearly the same image quality as a conventional stationary CT scanner

The use of mobile head CT scanners in the neurointensive care unit (NICU) saves time for patients and NICU staff and can reduce transport-related mishaps, but the reduced image quality of previous mobile scanners has prevented their widespread clinical use. This study compares the image quality of SOMATOM On.Site (Siemens Healthineers, Erlangen, Germany), a state-of-the-art mobile head CT scanner, and a conventional 64-slice stationary CT scanner. The study included 40 patients who underwent head scans with both mobile and stationary scanners. Gray and white matter signal and noise were measured at predefined locations on axial slices, and signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) were calculated. Artifacts below the cranial calvaria and in the posterior fossa were also measured. In addition, image quality was subjectively assessed by two radiologists in terms of corticomedullary differentiation, subcalvarial space, skull artifacts, and image noise. Quantitative measurements showed significantly higher image quality of the stationary CT scanner in terms of noise, SNR and CNR of gray and white matter. Artifacts measured in the posterior fossa were higher with the mobile CT scanner, but subcalvarial artifacts were comparable. Subjective image quality was rated similarly by two radiologists for both scanners in all domains except image noise, which was better for stationary CT scans. The image quality of the SOMATOM On.Site for brain scans is inferior to that of the conventional stationary scanner, but appears to be adequate for daily use in a clinical setting based on subjective ratings.